Model Peramalan Harga Kol/Kubis Tingkat Konsumen di Kabupaten Ngawi, Kabupaten Pacitan, Provinsi Jawa Timur, dan Indonesia

Rina Hikmawati; Reflis Reflis; Rama Fajarwanto; Tri Arrizki; Desi Karlina

doi:10.61132/jieap.v2i4.1801

Authors

Rina Hikmawati Universitas Bengkulu
Reflis Reflis Universitas Bengkulu
Rama Fajarwanto Universitas Bengkulu
Tri Arrizki Universitas Bengkulu
Desi Karlina Universitas Bengkulu

DOI:

https://doi.org/10.61132/jieap.v2i4.1801

Keywords:

Cabbage, Consumer, Forecast, Price, Trend

Abstract

This study aims to analyze and project consumer prices of cabbage commodities at four levels: Ngawi Regency, Pacitan Regency, East Java Province, and nationally, using the additive Holt–Winters forecasting model. Monthly price data for the period January 2020–December 2024 were used to capture the dynamics of levels, trends, and seasonal patterns that affect price fluctuations. Model performance was evaluated using the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) indicators. The results showed differences in model accuracy between regions. East Java Province produced the best performance with the lowest MAE and RMSE values, indicating a more stable price pattern that was easier for the model to capture. In contrast, Ngawi Regency showed the highest volatility, resulting in greater forecasting errors. Pacitan Regency displayed a relatively consistent seasonal pattern with moderate accuracy, while national data showed smoother fluctuations due to the aggregation effect. Overall, the additive Holt–Winters model is effective for short-term projections in regions with low to moderate variability, but is less optimal in regions with highly volatile price dynamics.

Downloads

Download data is not yet available.

References

Arsanti, I. W., Sayekti, A. L., & Kiloes, A. M. (2018). Analisis rantai nilai komoditas kubis (Brassica oleracea L): Studi kasus di sentra produksi Kabupaten Karo. Jurnal Hortikultura, 27(2), 269–278. https://doi.org/10.21082/jhort.v27n2.2017.p269-278

Badan Pusat Statistik. (2025). Republik Indonesia dalam Angka 2025. BPS.

Darmawan, S., Indriastiningsih, E., & Primasanti, Y. (2019). Analisa peramalan penjualan & pengendalian persediaan sparepart motor Honda Beat FI dengan metode EOQ di Graha Karya Ahass Cikarang 10827 (Doctoral dissertation). Universitas Sahid Surakarta.

Dewi, N. P., & Lisiowarni, I. (2020). Implementasi Holt-Winters exponential smoothing untuk peramalan harga bahan pangan di Kabupaten Pamekasan. Digital Zone: Jurnal Teknologi Informasi dan Komunikasi, 11(2), 223–236. https://doi.org/10.31849/digitalzone.v11i2.4797

Edi, S., & Bobihoe, Z. (2010). Budidaya tanaman sayuran. BPTP.

Fitria, D. N. (2024). Sistem harga hortikultura buah dan sayur. Deepublish.

Hartono, R. (2019). Price volatility of horticulture commodity during the harvest season. Habitat. Universitas Sriwijaya.

Hyndman, R. J., & Athanasopoulos, G. (2018). Forecasting: Principles and practice. Texts.

Istanto, I., Roessali, W., & Setiadi, A. (2016). Analisis pemasaran kubis (Brassica oleracea L. var. capitata L) di Sub Terminal Agribisnis (STA) Jetis Kabupaten Semarang. Mediagro: Jurnal Ilmu-Ilmu Pertanian, 12(2).

Kotler, P., & Armstrong, G. (2018). Principles of marketing (17th ed.). Pearson.

Makridakis, S., McGee, V. E., Hyndman, R. J., & Wheelwright, S. C. (1998). Forecasting: Methods and applications (3rd ed.). John Wiley & Sons.

Mamat. (2019). Least square method technique for predicting the acquisition of raw materials and sales of crisp for small and medium enterprises. Journal of Recent Technology and Engineering, 7(5), 612–616.

Matondang, M. R., Krisnamurthi, B., & Herawati. (2024). Price fluctuations and volatility of national strategic food commodities in Indonesia. Agrisocionomics. https://doi.org/10.14710/agrisocionomics.v8i1.17753

Mostafa, S. M., & Amano, H. (2019). Effect of clustering data in improving machine learning model accuracy. Journal of Theoretical and Applied Information Technology, 97(21), 2973–2981.

Nurani, A. T., Setiawan, A., & Susanto, B. (2023). Perbandingan kinerja regresi decision tree dan regresi linear berganda untuk prediksi BMI pada dataset asthma. Jurnal Sains dan Edukasi Sains, 6(1), 34–43. https://doi.org/10.24246/juses.v6i1p34-43

Pindyck, R. S., Rubinfeld, D. L., Hall, B. H., & Schmukler, S. L. (1998). TSP handbook to accompany Econometric Models and Economic Forecasts.

Priyanto, P., Widyastuti, Y., & Indrastianingrum, P. (2025). Identifikasi komoditas unggulan sayuran di Kabupaten Boyolali. AGROTECH Research Journal, 6(1), 19–24. https://doi.org/10.36596/arj.v6i1.1812

Rahmawati, A., & Fariyanti, A. (2018). Analisis risiko harga komoditas sayuran unggulan di Indonesia. Forum Agribisnis, 8(1), 35–60. https://doi.org/10.29244/fagb.8.1.35-60

Ramadhani, D., Suhartini, Nugroho, T. W., Muhaimin, A. W., & Wahyuningtyas, A. S. H. (2025). Dampak pembangunan infrastruktur pertanian terhadap kesejahteraan rumah tangga petani padi di Malang. Pangan, 34(1), 1–12.

Salsabila, P., & Wulandari, W. (2025). Kajian peran sektor pertanian dalam pembangunan ekonomi daerah di Nusa Tenggara Barat. Journal of Economics Development Research, 1(3), 102–112. https://doi.org/10.71094/joeder.v1i3.146

Siregar, Y. J., Hartono, R., & Hardana, A. E. (2022). Peramalan harga cabai rawit di Kota Malang dengan metode Holt-Winters exponential smoothing. Agricore: Jurnal Agribisnis dan Sosial Ekonomi Pertanian Unpad, 6(2). https://doi.org/10.24198/agricore.v6i2.34778

Sugiyono. (2022). Metode penelitian kuantitatif, kualitatif dan R&D. Alfabeta.

Suhaeni. (2025). Pengantar agribisnis dan ketahanan pangan.

Sukiyono, K., & Rosdiana, R. (2018). Pendugaan model peramalan harga beras pada tingkat grosir. Jurnal AGRISEP, 17(1), 23–30. https://doi.org/10.31186/jagrisep.17.1.23-30

Sun, C., Khan, A., & Ren, Y. (2023). Empowering progress: Education, innovations and financial development in the battle against energy poverty. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2023.138941

Suryanto, A. A. (2019). Penerapan metode mean absolute error (MAE) dalam algoritma regresi linear untuk prediksi produksi padi. SAINTEKBU, 11(1), 78–83. https://doi.org/10.32764/saintekbu.v11i1.298

Theresia, A., Ikhsan, M., Kacaribu, F. N., & Sumarto, S. (2025). Spillover effect of food producer price volatility in Indonesia. Economies, 13(9), 256. https://doi.org/10.3390/economies13090256

Tjiptono, F. (2015). Strategi pemasaran (2nd ed.). Andi Offset.